Decision aids for people with Type 2 diabetes mellitus: an effectiveness rapid review and meta‐analysis

Abstract

Aims To perform a rapid review and meta-analysis of randomized controlled trials (RCTs) evaluating patient decision aids (PtDAs) for people with Type 2 diabetes mellitus. Methods We searched Medline and the Cochrane Library for RCTs assessing PtDAs in people with Type 2 diabetes. PtDAs were defined as tools designed to help people engage in decision-making about healthcare options, such as making treatment choices or setting therapeutic goals. The study selection process was facilitated by an automated screening tool to identify RCTs. We classified outcomes into seven domains and conducted meta-analyses using random effects models. Results We included a total of 15 studies, nine of which were cluster RCTs, that evaluated 10 PtDAs. Thirteen trials compared a PtDA with usual care or usual care plus educational material, whereas two RCTs compared individually tailored vs. non-tailored PtDAs. Meta-analyses showed a favourable effect of PtDAs compared with usual care in reducing decisional conflict [weighted mean difference (WMD) À4.66, 95% confidence interval (CI) À7.93 to À1.39] and in improving knowledge (WMD 20.46, 95% CI 9.13 to 3.77). Use of PtDAs resulted in more active involvement in decision-making during the consultation, although no effect was evident in terms of glycaemic control or self-reported medication adherence.Conclusions PtDAs for people with Type 2 diabetes can improve the quality of decision-making and increase knowledge transfer. Interpretation of our findings is attenuated due to limitations related to the rapid review approach, including searching only two databases and performing data extraction and risk of bias assessment by a single reviewer. DIABETICMedicineMeta-analysis of decision aids for people with Type 2 diabetes T. Karagiannis et al.

Automated Screener Based on Convolutional Neural Network for Randomized Controlled Trials in Chinese Language: A Comparative Study of Different Classification Strategies

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Use of artificial intelligence for management and identification of complications in diabetes

“…neuropathy, retinopathy, nephropathy, diabetic foot, stroke, cardiovascular and peripheral vascular diseases) for improvement of the QoL. Patient decision-support aids have been used for various purposes for decision making in people with diabetes about options like the treatment choices or setting the therapeutic goals and have been proven in improving the quality of decision making and increase of knowledge transfer [7]. The amount of data each person living with diabetes can generate is huge and can amount to 1 million gigabytes but most of the data is unstructured [5].…”

Effects of patient decision aids in patients with type 2 diabetes mellitus: A systematic review and meta‐analysis

“…Although a number of PtDAs related to aspects of diabetic disease have been evaluated, there has been no review of the overall efficacy on these PtDAs in diabetes. A recent article (Karagiannis et al, 2019) revealed that PtDA had a significant effect on reducing decisional conflict and improving knowledge among patients with T2DM. However, this meta‐analysis implemented a rapid review approach, which only searched two major databases, and risk of bias assessment by a single reviewer.…”